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Lookup NU author(s): Kim Keltie, Dr Paola Cognigni, Dr Sam Urwin, Dr Andrew SimsORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. Objectives: The UK MitraClip registry was commissioned by National Health Service (NHS) England to assess real-world outcomes from percutaneous mitral valve repair for mitral regurgitation using a new technology, MitraClip. This study aimed to determine longitudinal patient outcomes by linking to routine datasets: Hospital Episode Statistics (HES) Admitted Patient Care (APC) and Office of National Statistics. Methods Two methods of linkage were compared, using identifiable (NHS number, date of birth, postcode, gender) and non-identifiable data (hospital trust, age in years, admission, discharge and operation dates, operation and diagnosis codes). Outcome measures included: matching success, patient demographics, all-cause mortality and subsequent cardiac intervention. Results: A total of 197 registry patients were eligible for matching with routine administrative data. Using identifiable linkage, a total of 187 patients (94.9%) were matched with the HES APC dataset. However, 21 matched individuals (11.2%) had inconsistencies across the datasets (eg, different gender) and were subsequently removed, leaving 166 (84.3%) for analysis. Using non-identifiable data linkage, a total of 170 patients (86.3%) were uniquely matched with the HES APC dataset. Baseline patient characteristics were not significantly different between the two methods of data linkage. The total number of deaths (all causes) identified from identifiable and non-identifiable linkage methods was 37 and 40, respectively, and the difference in subsequent cardiac interventions identified between the two methods was negligible. Conclusions: Patients from a bespoke clinical procedural registry were matched to routine administrative data using identifiable and non-identifiable methods with equivalent matching success rates, similar baseline characteristics and similar 2-year outcomes.
Author(s): Keltie K, Cognigni P, Gross S, Urwin S, Burn J, Cole H, Berry L, Patrick H, Sims A
Publication type: Article
Publication status: Published
Journal: BMJ Health and Care Informatics
Year: 2021
Volume: 28
Issue: 1
Online publication date: 05/04/2021
Acceptance date: 08/03/2021
Date deposited: 22/04/2021
ISSN (electronic): 2632-1009
Publisher: BMJ Publishing Group
URL: https://doi.org/10.1136/bmjhci-2020-100223
DOI: 10.1136/bmjhci-2020-100223
PubMed id: 33820808
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